statLimma: Statistical testing with limma

In pmoulos/metaseqR2-local: An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

Statistical testing with limma

Description

This function is a wrapper over limma statistical testing. It accepts a matrix of normalized gene counts or an S4 object specific to each normalization algorithm supported by metaseqR2.

Usage

    statLimma(object, sampleList, contrastList = NULL,
        statArgs = NULL)

Arguments

object	a matrix or an object specific to each normalization algorithm supported by metaseqR2, containing normalized counts. See also Details.
sampleList	the list containing condition names and the samples under each condition.
contrastList	vector of contrasts as defined in the main help page of metaseqr2. See also Details.
statArgs	a list of edgeR statistical algorithm parameters. See the result of getDefaults("statistics", "limma") for an example and how you can modify it.

Details

Regarding object, apart from matrix (also for NOISeq), the object can be a SeqExpressionSet (EDASeq), CountDataSet (DESeq), DGEList (edgeR), DESeqDataSet (DESeq2), SeqCountSet (DSS) or ABSDataSet (ABSSeq).

Regarding contrastList it can also be a named structured list of contrasts as returned by the internal function metaseqR2:::makeContrastList.

Value

A named list of p-values, whose names are the names of the contrasts.

Author(s)

Panagiotis Moulos

Examples

require(limma)
dataMatrix <- metaseqR2:::exampleCountData(2000)
sampleList <- list(A=c("A1","A2"),B=c("B1","B2","B3"))
contrast <- "A_vs_B"
normDataMatrix <- normalizeEdger(dataMatrix,sampleList)
p <- statLimma(normDataMatrix,sampleList,contrast)

pmoulos/metaseqR2-local documentation built on May 21, 2024, 3:46 a.m.